Cryptography is an indispensable tool for protecting information in computer systems. In this course you will learn the inner workings of cryptographic systems and how to correctly use them in real-world applications. The course begins with a detailed discussion of how two parties who have a shared secret key can communicate securely when a powerful adversary eavesdrops and tampers with traffic. We will examine many deployed protocols and analyze mistakes in existing systems. The second half of the course discusses public-key techniques that let two parties generate a shared secret key. Throughout the course participants will be exposed to many exciting open problems in the field and work on fun (optional) programming projects. In a second course (Crypto II) we will cover more advanced cryptographic tasks such as zero-knowledge, privacy mechanisms, and other forms of encryption.
Key Derivation
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Del curso dictado por Stanford University
Cryptography I
2510 calificaciones
De la lección
Authenticated Encryption
Week 4. This week's topic is authenticated encryption: encryption methods that ensure both confidentiality and integrity. We will also discuss a few odds and ends such as how to search on encrypted data. This is our last week studying symmetric encryption. Next week we start with key management and public-key cryptography. As usual there is also an extra credit programming project. This week's project involves a bit of networking to experiment with a chosen ciphertext attack on a toy web site.
Conoce a los instructores
Dan BonehProfessor
Computer Science
Well, we're almost done with our discussion of symmetric encryption. There
are just a couple of odds and ends that I'd like to discuss before we move on to
the next topic. So the first thing I'd like to mention is how we derive many keys
from one key. And it, actually, this comes up all the time in practice, so I'd like
to make sure you know how to do this correctly. So what's the setting that
we're looking at? Well, imagine we have a certain source key that's generated by one
of, a number of methods. Imagine the source key is generated by a hardware
random number generator or perhaps is generated by a key exchange protocol
which we're going to discuss later. But anyhow, there are a number of ways in
which a source key might be generated between Alice and Bob, such that the
attacker doesn't know what the source key is. But now, as we said, in many cases, we
actually need many keys to secure a session, not just one single source key.
For example, if you remember, in TLS there were unidirectional keys and we
needed keys in each direction. And in fact, in each direction, we needed
multiple keys. We needed a MAC key, we needed an encryption key. We need an IV,
and so on. Similarly nonce based encryption, you remember, there were
multiple keys that were being used, and so on. And so, the question is, how do we use
the one source key that we just derived, either from a hardware process or
by key exchange, and generate a bunch of keys from it that we could then use to
secure our session. The way that's done, is using a mechanism called a key
derivation function, KDF. And I want to talk a little bit about how KDF's are
constructed. So first of all, suppose we have a secure PRF, that happens to have
key space K. And now, suppose that it so happens that our source key SK is uniform
in the key K. In this case, the source key is, in fact, a uniform random key for the
secure PRF F. And we can use it directly to generate keys, all the keys that we need
to secure the session. So in this case, the KDF is really simple. The key
derivation function would just work as follows. It would take as input the
source key. It would take an input, a parameter context, which I'm gonna
describe in just a minute. And then it's gonna take a length input as input as
well. And then what it will do is it will basically evaluate the PRF on zero. Then
it will evaluate the PRF on one. Then it will evaluate the PRF on two, up until L.
And I will talk about what this context is in just a second. And then, basically, you
would use as many bits of the output as you would need to generate all the keys
for the session. So, if you need unidirectional keys you would generate, you
know, one key in each direction where each key might include an encryption key and a MAC
key. And so, you would basically generate as many bits as you need and then finally
cut off the output at the time when you've generated enough keys to secure your
session. Okay so this is a fairly straight forward mechanism it's basically using the
secure PRF as a pseudo random generator. And the only question is what is its
context string. Well, I'll tell you that the context string is basically a unique
string that identifies the application. So in fact you might have multiple
applications on the same system that's trying to establish multiple secure keys.
Maybe you have SSH running as one process, you have a web server running as another process,
IPsec as a third process and all three need to have secret keys generated. And this
context variable basically tries to separate the three of them. So, let me ask you,
more precisely, what do you think the purpose of this context variable is?
So I guess I've given it away and this context variable is
supposed to basically separate applications, so that even if, for
example, the three services that we just talked about, SSH, web server, and IPsec,
if they all happen to obtain the same source key from the hardware random number
generator then the context since it's different for the three apps will make
sure that they still get three independent strings that they can then use to secure
the sessions. I just want you to remember that, even though this is actually fairly
straightforward, and we discussed this before, the context string is actually
important, and it does need to be specific to the application, so that each
application gets its own session keys, even if multiple applications happen to
sample the same SK. The next question is, what do we do if the source
key actually isn't uniform? Well, now we got a problem. If the source key is not a
uniform key for the pseudo random function then we can no longer assume that the
output of the pseudo random function is indistinguishable from random. In fact, if
we just use the KDF that we just described then the output might not look random to
the adversary and then he might be able to anticipate some of the session keys that
we'll be using and thereby break the session. So then we have a problem. Now
why would this source key not be uniform? Well there are many reasons why this
happened. For example if you use a key exchange protocol, it so happens typically
that key exchange protocols will generate a high entropy key. But the
high entropy key is gonna be distributed in some subspace of the key
space. So it's not going to be a uniform string. It will be uniform in some
subset of a larger set, And we'll see examples of that as soon as we talk about
key exchange protocols. And so KDFs have to kind of accommodate for the fact that
key exchange protocols actually don't generate uniform bit strings. The other
problem is, that, in fact, the hardware random number generator you're using might
actually produce biased outputs. We don't wanna rely on the non bias of the hardware
random number generator. And so all we want to assume is that it generates a high
entropy string, but one that might be biased. In which case, we have to somehow
clean this bias. And so this introduces this, this paradigm for building KDFs.
This is called the extract-then-expand paradigm, where the first step
of the KDF is to extract a pseudo random key from the actual source key. So in a
picture you can think about it like this. In some sense these are the different
possible values of the source key. This is the horizontal line and the vertical axis
is basically the probability of each one of these values, and you can see that this
is a kind of a bumpy function which would say that the source key is not uniformly
distributed in the key space. What we do in this case is we use what's called an
extractor. So an extractor is something that takes a bumpy distribution and makes
it into a uniform distribution over the key space. In our case we're actually just
gonna be using what are called computational extractors, namely
extractors that don't necessarily produce uniform distribution at the end but
they generated distribution that's indistinguishable from uniform.
Now extractors typically take as input something called a salt, and a salt just
like in a salad, it kind of adds flavor to things, what it does is basically kind of
jumbles things around, so that no matter what the input distribution is, the output
distribution is still going to be indistinguishable from random. So a salt
basically, what is it? It's a non-secret string, so it's publicly known. It doesn't
matter if the adversary knows what the salt is, and it's fixed forever. The only
point is that when you chose it, you chose one at random. And then the hope is that
the funny distribution that you're trying to extract from kinda doesn't inherently
depends on the salt that you chose and hence as a result using your salt, you
will actually get a distribution that looks indistinguishable from random. So
essentially the salt, you know, you can just bang it the keyboard a couple of
times when you generate it but it just needs to be something that's random
initially but then it's fixed forever, and it's fine if the adversary knows what
it is and nevertheless the extractor is able to extract the entropy and output a
uniformly random string K. In some sense the salt is only there to defend against
adversarially bad distributions that might mess up our extractor. Okay, so now that
we have extracted a pseudo random key. Now, we might as well just use it in a KDF
that we just saw using a secure pseudo random function to expand the key
into as many bits as we need to actually secure the session. Okay, so there are
these two steps. The first one is we extract a pseudo-random key, and then once
we have a pseudo-random key we already know how to extend it into as many keys as
we need using a pseudo-random function. So the standardized way of doing this is
called HKDF. This is a KDF, a key derivation function that's built from HMAC.
And here HMAC is used both as the PRF for expanding and an extractor for extracting
the initial pseudo-random key. So let me explain how this works. So in the extract
step, we're gonna use our salt which you remember is a public value just happened to
be generated at random at the beginning of time. And we use this salt as the HMAC
key. And then the source key we're gonna use as the HMAC data. So we're kind of
using a public value as a key. And nevertheless, one can argue that HMAC has
extraction properties, such that, when we apply HMAC, the resulting key is going to
look indistinguishable from random, assuming that the source key actually has
enough entropy to it. And now that we have the pseudo random key we're simply going
to use HMAC as a PRF to generate a session key of you know as many bits as we
need for the session keys. Okay. So that basically concludes our discussion of
HKDF. And I just want you to remember that, once you obtain a source key, either
from hardware or from a key exchange protocol, the way you convert it into
session keys is not by using that sample directly. You would never use a source key
directly as a session key in a protocol. What you would do is you will run the
source key through a KDF. And the KDF would give you all the keys and output
that you need, for, the randomness, for the random keys to be used in your
protocol. And a typical KDF to use is HKDF, which is actually getting quite a
bit of traction out there. Okay. The last topic I wanna talk about in this segment
is, how do you extract keys from passwords. These are called password based
KDFs or PBKDFs. The problem here is that passwords have relatively low
entropy. In fact, we're gonna talk about passwords later on in the course when we
talk about user authentication. And so, I'm not gonna say too much here. I'll just
say passwords generally have very little entropy estimated on the order of twenty
bits of entropy, say. And as a result, there is simply not enough entropy to
generate session keys out of a password. And yet we still need to do it very
frequently. We still need to derive encryption keys and MACs and so on out of
passwords, so the question is how to do it. The first thing is, you know, for this
kind of purpose, don't use HKDF. That's not what it's designed for. What will
happen is that the derived keys will actually be vulnerable to something called
a dictionary attack, which we're gonna talk about much later in the course when
we talk about user authentication. So, the way PBKDFs defend against this low entropy
problem that results in a dictionary attack is by two means. First of all, as
before they use a salt, a public, random value that's fixed forever. But in
addition, they also use what's called a slow hash function. And let me describe
kind of the standard approach to deriving keys from passwords. This is called PKCS#5,
and in particular, the version I'll describe is what's called PBKDF1. And I
should say that this mechanism is implemented in most crypto libraries so
you shouldn't have to implement this yourself. All you would do, you know, you
would call a function, you know, derived key from password. You would give the
password in as input, and you would get a key as output. But you should be aware of
course that this key is not going to have high entropy so in fact it will be
guessable. What these PBKDFs try to do is make the guessing problem as hard as
possible. Okay. So the way they work, first of all, is, as we said, they
basically hash, the concatenation of the password and the salt. And then the hash
itself is designed to be a very slow hash function. And the way we build a slow hash
function is by taking one particular hash function, say, SHA-256, and we
iterate it many, many times, C times. So you can imagine 1000 times, perhaps even a
million times. And what do I mean by iterating it? So, well, we take the
password and the salt. And we put them inside of one input to the hash function.
And then we apply the hash function, oops, let me write it like this. And then we
apply the hash function and we get an output, and then we apply the hash
function again and we get another output. And we do this again and again and again
maybe a thousand times or a million times depending on how fast your processors are
and then finally we get the final output that we actually output as, as the key
output of this key derivation function. Now what is the point here? Iterating a
function 10,000 times or even a million times is going to take very little time on
a modern CPU, and as a result, it doesn't really affect the user's experience. The
user types in his password, it gets hashed a million times and then it gets output.
And maybe that could even take, you know a tenth of a second and the user wouldn't
even notice it. However the attacker, all he can do is he can try all the passwords
in the dictionary, because we know people tend to pick passwords in dictionaries,
and so he could just try them one by one, remember the SALT is public, so he knows
what the SALT is. And so he can just try this hash one by one. However because the hash
function is slow, each attempt is gonna take him a tenth of second. So if he needs
to run through a dictionary, you know, with, with a 200 billion passwords in it,
because the hash function is slow, this is gonna take quite awhile. And by doing
that, we slow down the dictionary attack, and we make it harder for the attacker to
get our session keys. Not impossible, just harder. That's all this is trying to do.
Okay, so this is basically what I wanted to say about password based KDFs. As I
said, this is not something you would build yourself. All crypto libraries have
an implementation of a PKCS#5 mechanism. And you would just call the
appropriate function to convert a password into a key, and then use the resulting
key. Okay, in the next segment, we're gonna see how to use symmetric encryption
in a way that allows us to search on the cipher texts.
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